A multisided platform business model is a company that leverages multisided network effects (coming from two or more sides of the network). Therefore, when one side of the network grows, this makes the overall platform more valuable for the other side of the network and vice-versa, triggering exponential growth for the platform business.
- Understanding platform business models
- Understanding network effects
- The multi-sided platform DNA
- Related Business Model Types
Understanding platform business models
In short, there are a few elements that define a platform business model:
Interactions vs. sales
A platform business model focuses on enabling an underlying ecosystem of third-party players that can build their own companies on top of the platform.
In short, the platform business is more concerned about the health of the overall entrepreneurial ecosystem, underlying it, that the sales of its own products.
In fact, oftentimes, for platform business models, most products and services sold, on top of it, are by third parties.
While, if the platform enables services, then it will collect a tax from one side, both sides, or multiple sides of the transactions (see Uber business model or Uber Eats business model, and Airbnb business model).
Transactions between the main parties of the network
Usually, a platform business model measures its financial success according to the gross value of the overall transactions happening on the platform.
Take the Airbnb business model economics. The company enables a gross booking value of almost $47 billion in 2021.
As a consequence of that, it generated an almost $6 billion tax, in service revenues.
One user type network improvement, also exponentially improves the other sides of the network
A platform’s network is highly interconnected. This means that by improving a side of the network, you also improve the other side.
However, often, when platform business models kick off their operations, they need to figure out which side of the network, they need to kick off first.
For instance, in the case of Uber Eats, the choice was simple. Since the company had already millions of drivers and users, it only needed to add restaurants/partners to kick off the whole network.
Instead, if you take the case of Uber, initially, to make its network valuable in the first place, it had to pick one side of the network: drivers.
In fact, as drivers became available, the company could kick off its network effects, by offering rides across various neighborhoods, cities, and countries, at competitive rates, and low wait times.
Flywheel vs. funnel
Where the sales funnel is used with a linear logic (and more in line with traditional organizations). When it comes to platform businesses, it’s all about feedback loops.
Those feedback loops move in all directions, as they help the network solidify.
Thus, as a platform, it’s critical to think in terms of flywheels rather than funnels.
This leads us to another key point.
Growth engines, vs. business development
Indeed, think of the case of Uber Eats which needs to go out and find a restaurant network and partners willing to join the platform.
This is a complex deal, which requires experienced business people, able to navigate the deal and unlock it.
Once these deals are closed, while business development (especially for platform leveraging enterprise customers) will be an integrated part of the overall business model, growth engines become critical.
Take the case of the Amazon e-commerce platform, with millions of freely accessible product pages, which prompt billion of users to see them. The underlying platform is both a technical platform, supporting thousands and thousands of third-party stores and a distribution engine!
Understanding network effects
In the table below, we structured how network effects are kicked off:
|Definition Network Effects: The value of a service/platform increases for each additional user, as more users, join in.||Sub-type||Description – Example|
|Direct, Same Side, or One-Sided||As more users join, the platform’s value increases for each additional user. Take the case of a social media platform, like Facebook, Instagram, TikTok, LinkedIn, Twitter. The more users join, the more the platform will be valuable for each additional user, as the new user might find exponentially richer and broader content (provided the platform can prevent congestion or pollution).|
|Indirect or Cross-Side||In this case, a user type joining the platform makes it more valuable for other user types. Take the case of LinkedIn. While LinkedIn enjoys the same-side network effects, the platform becomes more valuable to users looking to enhance their careers as more users join in. At the same time, LinkedIn enjoys indirect or cross-side network effects. More users who join the platform to grow their career make it more valuable for recruiters (so a different user type) as they can find more qualified candidates on top of the platform.|
|Two-Sided||Take the case of LinkedIn. While LinkedIn enjoys the same-side network effects, the platform becomes more valuable to users looking to enhance their careers as more users join in. At the same time, LinkedIn enjoys indirect or cross-side network effects. In this case, a user type joining the platform makes it more valuable for other user types. More users who join the platform to grow their career make it more valuable for recruiters (so a different user type) as they can find more qualified candidates on top of the platform.|
|Multi-Sided||In this case, more than two user types are driven by the network dynamics. Take the case of Uber Eats; the more restaurants join the platform, the more the platform becomes valuable for eaters. While at the same time, by leveraging its existing platform, Uber drivers have additional riding options. So they can earn extra income by delivering food instead of giving rides. That makes the overall platform much more valuable for the three main user types: eaters, restaurants, and riders.|
Below, instead we explain the curse of platform business models: negative network effects:
|Definition Negative Network Effects: The Value of the service/platform decreases for each additional user, as more users join in. This might be due to congestion (when increased usage can’t be handled by the platform) or pollution (when the increased size of the network makes it hard to incrementally add value, and instead its value shrinks).||Description – Example|
|Congestion (Increased Usage)||In this case, there is a reduced quality of the service when certain parts of the networks carry way more data than they can handle. That usually happens because of scale limitations and noise due to curation limitations. Since this is a technological issue, it manifests as service slowdown or perhaps the platform crashing. Take the case of services like YouTube crashing for too much traffic. Or, if you’re a professional, a service like Slack crashes as it cannot handle the traffic spikes. That becomes a disservice with potential negative network effects because you suddenly prevent a whole team from functioning properly. Therefore, a negative network effect can have exponential negative consequences. For instance, users would switch to alternatives en masse if this was repeatedly happening, thus creating structural damage to the network.|
|Network Pollution (Increased Size)||The case of pollution is more tied to the ability of the platform to keep its service relevant at scale. Thus, imagine the case of a platform like Twitter, in which the principal asset is the feed. As Twitter becomes more and more popular, it needs to make sure that the user-generated content is qualitatively on target. Otherwise, the risk is for the user’s Twitter feed to become less relevant and lose value. Or imagine the case that many user-generated platforms face today, where spambots take over. Here, suppose the platform cannot handle this automatically generated content. In that case, it can quickly lose value, as the service becomes worthless for users (take the case of a user who has to spend an hour a day cleaning up the feed because of spamming).|
The multi-sided platform DNA
Let’s see two case studies and examples of multi-sided platform business models.
LinkedIn Case Study
Take the example of LinkedIn, a platform for job seekers and recruiters.
Here the network effects dynamics are multi-sided, meaning that for more job seekers join LinkedIn, and enrich their profiles, the more the platform becomes valuable to recruiters.
And the more recruiters/companies join, the more the platform is valuable to job seekers.
Uber Eats Case Study
Another example is Uber Eats, in which complex dynamics between eaters, drivers, and restaurants/partners, enable the company to leverage multi-sied network effects to grow the company.
Complimentary Case Studies:
- Amazon Business Model
- Uber Business Model
- Uber Eats Business Model
- Airbnb Business Model
- LinkedIn Business Model